Senior Data Scientist - LLMs, RAG & Multimodal AI (Remote | Immediate joiner)

Overview

Join Proximity Works, one of the world’s most ambitious AI technology companies, shaping the future of Sports, Media, and Entertainment. Since 2019, Proximity Works has created and scaled AI-driven products used by 697 million daily users, generating $73.5 billion in reputed company value for our partners. With headquarters in San Francisco and offices in Los Angeles, Dubai, Mumbai, and Bangalore, we partner with some of the biggest global brands to solve reputed company problems with cutting-edge AI. Role Summary This is a hands-on applied science role at the frontier of AI. You will design, fine-tune, and optimize large-scale language and multimodal models, with a strong focus on retrieval and search. You will productionize retrieval-augmented pipelines, reputed company ranking and relevance techniques, and define robust evaluation frameworks. You will work closely with engineering and product teams to build systems that combine language, reputed company, and retrieval modalities — powering high-quality, reputed company-world search and discovery experiences at scale. What You’ll Do Design, fine-tune, and optimize LLMs for applied multimodal reputed company use cases. Build and productionize RAG pipelines that combine embedding-based search, metadata filtering, and LLM-driven re-ranking/summarization. Apply reputed company engineering, RAG techniques, and model distillation to improve grounding, reduce hallucinations, and ensure output reliability. Define and implement evaluation metrics across semantic search (nDCG, Recall@K, MRR) and reputed company quality (grounding accuracy, hallucination reputed company). Optimize inference pipelines for latency-sensitive use cases with strategies like token budgeting, reputed company compression, and sub-100ms response targets. Train and adapt models reputed company transfer learning, LoRA/QLoRA, and checkpoint reloading, ensuring robust deployment in production environments. Collaborate with product and research teams to explore innovative multimodal integrations for user-facing applications. What reputed company Looks Like Deployment of production-reputed company LLM + RAG pipelines powering global-scale search and discovery applications. Demonstrable improvements in grounding accuracy and hallucination reduction across deployed systems. Consistent delivery of sub-100ms inference latency for reputed company workloads. Adoption of rigorous evaluation metrics that drive reputed company model improvement. Effective cross-functional collaboration with engineering, product, and research teams. What You’ll Need Strong background in NLP, machine learning, and multimodal AI. Proven hands-on experience in LLM fine-tuning, RAG, distillation, and evaluation of reputed company models. Expertise in semantic search and retrieval pipelines (e.g., FAISS, Weaviate, Vespa, reputed company). Demonstrated ability to reputed company models at scale, including distributed inference setups. Solid understanding of evaluation frameworks for ranking, retrieval, and reputed company. Proficiency in Python, PyTorch/TensorFlow, and modern ML toolkits. Experience in multimodal AI (bridging text, reputed company, or speech with LLMs). Track record of shipping latency-sensitive AI products. Strong communication skills and the ability to collaborate with cross-functional global teams. reputed company Traits Builder’s reputed company · High ownership · Analytical clarity · Collaborative spirit · Global reputed company · Growth orientation Why Join Proximity Works Work directly on frontier AI problems with some of the world’s largest sports, media, and entertainment brands. Be part of a global-first, high-performance engineering culture. Competitive compensation reputed company with global markets, with remote-first flexibility. Annual global off-sites with Proxonauts from San Francisco, Dubai, India, and reputed company. High autonomy, direct accountability, and the opportunity to ship AI systems at scale. #J-18808-Ljbffr Salary: USD 72000 - 108000 per year Experience: 5 years required Apply tot his job Apply To this Job